Overview

Dataset statistics

Number of variables20
Number of observations338592
Missing cells0
Missing cells (%)0.0%
Duplicate rows328980
Duplicate rows (%)97.2%
Total size in memory51.7 MiB
Average record size in memory160.0 B

Variable types

Categorical8
Numeric12

Warnings

Dataset has 328980 (97.2%) duplicate rows Duplicates
Jyotai11Chakukaisu6 has 329843 (97.4%) zeros Zeros
Kyori1Chakukaisu1 has 270618 (79.9%) zeros Zeros
Kyori1Chakukaisu2 has 274489 (81.1%) zeros Zeros
Kyori1Chakukaisu3 has 269400 (79.6%) zeros Zeros
Kyori1Chakukaisu4 has 268465 (79.3%) zeros Zeros
Kyori1Chakukaisu5 has 266290 (78.6%) zeros Zeros
Kyori1Chakukaisu6 has 123166 (36.4%) zeros Zeros
Kyori2Chakukaisu1 has 282190 (83.3%) zeros Zeros
Kyori2Chakukaisu2 has 285898 (84.4%) zeros Zeros
Kyori2Chakukaisu3 has 282762 (83.5%) zeros Zeros
Kyori2Chakukaisu4 has 280426 (82.8%) zeros Zeros
Kyori2Chakukaisu5 has 279296 (82.5%) zeros Zeros

Reproduction

Analysis started2021-04-07 13:25:45.606193
Analysis finished2021-04-07 13:27:13.818307
Duration1 minute and 28.21 seconds
Software versionpandas-profiling v2.11.0
Download configurationconfig.yaml

Variables

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
0
336837 
1
 
1687
2
 
68

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters338592
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0336837
99.5%
11687
 
0.5%
268
 
< 0.1%
Histogram of lengths of the category
ValueCountFrequency (%)
0336837
99.5%
11687
 
0.5%
268
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0336837
99.5%
11687
 
0.5%
268
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number338592
100.0%

Most frequent character per category

ValueCountFrequency (%)
0336837
99.5%
11687
 
0.5%
268
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common338592
100.0%

Most frequent character per script

ValueCountFrequency (%)
0336837
99.5%
11687
 
0.5%
268
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII338592
100.0%

Most frequent character per block

ValueCountFrequency (%)
0336837
99.5%
11687
 
0.5%
268
 
< 0.1%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
0
336914 
1
 
1651
2
 
25
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters338592
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0336914
99.5%
11651
 
0.5%
225
 
< 0.1%
32
 
< 0.1%
Histogram of lengths of the category
ValueCountFrequency (%)
0336914
99.5%
11651
 
0.5%
225
 
< 0.1%
32
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0336914
99.5%
11651
 
0.5%
225
 
< 0.1%
32
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number338592
100.0%

Most frequent character per category

ValueCountFrequency (%)
0336914
99.5%
11651
 
0.5%
225
 
< 0.1%
32
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common338592
100.0%

Most frequent character per script

ValueCountFrequency (%)
0336914
99.5%
11651
 
0.5%
225
 
< 0.1%
32
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII338592
100.0%

Most frequent character per block

ValueCountFrequency (%)
0336914
99.5%
11651
 
0.5%
225
 
< 0.1%
32
 
< 0.1%

Jyotai11Chakukaisu6
Real number (ℝ≥0)

ZEROS

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03260856724
Minimum0
Maximum5
Zeros329843
Zeros (%)97.4%
Memory size2.6 MiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2230872409
Coefficient of variation (CV)6.841368996
Kurtosis103.1163769
Mean0.03260856724
Median Absolute Deviation (MAD)0
Skewness8.964321436
Sum11041
Variance0.04976791707
MonotocityNot monotonic
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0329843
97.4%
17084
 
2.1%
21195
 
0.4%
3322
 
0.1%
4139
 
< 0.1%
59
 
< 0.1%
ValueCountFrequency (%)
0329843
97.4%
17084
 
2.1%
21195
 
0.4%
3322
 
0.1%
4139
 
< 0.1%
ValueCountFrequency (%)
59
 
< 0.1%
4139
 
< 0.1%
3322
 
0.1%
21195
 
0.4%
17084
2.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
0
337691 
1
 
895
3
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters338592
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0337691
99.7%
1895
 
0.3%
36
 
< 0.1%
Histogram of lengths of the category
ValueCountFrequency (%)
0337691
99.7%
1895
 
0.3%
36
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0337691
99.7%
1895
 
0.3%
36
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number338592
100.0%

Most frequent character per category

ValueCountFrequency (%)
0337691
99.7%
1895
 
0.3%
36
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common338592
100.0%

Most frequent character per script

ValueCountFrequency (%)
0337691
99.7%
1895
 
0.3%
36
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII338592
100.0%

Most frequent character per block

ValueCountFrequency (%)
0337691
99.7%
1895
 
0.3%
36
 
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
0
337563 
1
 
998
2
 
31

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters338592
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0337563
99.7%
1998
 
0.3%
231
 
< 0.1%
Histogram of lengths of the category
ValueCountFrequency (%)
0337563
99.7%
1998
 
0.3%
231
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0337563
99.7%
1998
 
0.3%
231
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number338592
100.0%

Most frequent character per category

ValueCountFrequency (%)
0337563
99.7%
1998
 
0.3%
231
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common338592
100.0%

Most frequent character per script

ValueCountFrequency (%)
0337563
99.7%
1998
 
0.3%
231
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII338592
100.0%

Most frequent character per block

ValueCountFrequency (%)
0337563
99.7%
1998
 
0.3%
231
 
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
0
337575 
1
 
980
3
 
37

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters338592
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0337575
99.7%
1980
 
0.3%
337
 
< 0.1%
Histogram of lengths of the category
ValueCountFrequency (%)
0337575
99.7%
1980
 
0.3%
337
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0337575
99.7%
1980
 
0.3%
337
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number338592
100.0%

Most frequent character per category

ValueCountFrequency (%)
0337575
99.7%
1980
 
0.3%
337
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common338592
100.0%

Most frequent character per script

ValueCountFrequency (%)
0337575
99.7%
1980
 
0.3%
337
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII338592
100.0%

Most frequent character per block

ValueCountFrequency (%)
0337575
99.7%
1980
 
0.3%
337
 
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
0
337755 
1
 
814
2
 
23

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters338592
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0337755
99.8%
1814
 
0.2%
223
 
< 0.1%
Histogram of lengths of the category
ValueCountFrequency (%)
0337755
99.8%
1814
 
0.2%
223
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0337755
99.8%
1814
 
0.2%
223
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number338592
100.0%

Most frequent character per category

ValueCountFrequency (%)
0337755
99.8%
1814
 
0.2%
223
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common338592
100.0%

Most frequent character per script

ValueCountFrequency (%)
0337755
99.8%
1814
 
0.2%
223
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII338592
100.0%

Most frequent character per block

ValueCountFrequency (%)
0337755
99.8%
1814
 
0.2%
223
 
< 0.1%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
0
337679 
1
 
881
2
 
32

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters338592
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0337679
99.7%
1881
 
0.3%
232
 
< 0.1%
Histogram of lengths of the category
ValueCountFrequency (%)
0337679
99.7%
1881
 
0.3%
232
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0337679
99.7%
1881
 
0.3%
232
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number338592
100.0%

Most frequent character per category

ValueCountFrequency (%)
0337679
99.7%
1881
 
0.3%
232
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common338592
100.0%

Most frequent character per script

ValueCountFrequency (%)
0337679
99.7%
1881
 
0.3%
232
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII338592
100.0%

Most frequent character per block

ValueCountFrequency (%)
0337679
99.7%
1881
 
0.3%
232
 
< 0.1%
Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
0
333776 
1
 
4243
2
 
458
3
 
114
5
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters338592
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0333776
98.6%
14243
 
1.3%
2458
 
0.1%
3114
 
< 0.1%
51
 
< 0.1%
Histogram of lengths of the category
ValueCountFrequency (%)
0333776
98.6%
14243
 
1.3%
2458
 
0.1%
3114
 
< 0.1%
51
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0333776
98.6%
14243
 
1.3%
2458
 
0.1%
3114
 
< 0.1%
51
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number338592
100.0%

Most frequent character per category

ValueCountFrequency (%)
0333776
98.6%
14243
 
1.3%
2458
 
0.1%
3114
 
< 0.1%
51
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common338592
100.0%

Most frequent character per script

ValueCountFrequency (%)
0333776
98.6%
14243
 
1.3%
2458
 
0.1%
3114
 
< 0.1%
51
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII338592
100.0%

Most frequent character per block

ValueCountFrequency (%)
0333776
98.6%
14243
 
1.3%
2458
 
0.1%
3114
 
< 0.1%
51
 
< 0.1%

Kyori1Chakukaisu1
Real number (ℝ≥0)

ZEROS

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4244341272
Minimum0
Maximum12
Zeros270618
Zeros (%)79.9%
Memory size2.6 MiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum12
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.071378848
Coefficient of variation (CV)2.524252361
Kurtosis12.959152
Mean0.4244341272
Median Absolute Deviation (MAD)0
Skewness3.322648517
Sum143710
Variance1.147852635
MonotocityNot monotonic
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0270618
79.9%
132878
 
9.7%
214989
 
4.4%
38993
 
2.7%
45844
 
1.7%
52695
 
0.8%
61573
 
0.5%
7649
 
0.2%
8219
 
0.1%
983
 
< 0.1%
Other values (3)51
 
< 0.1%
ValueCountFrequency (%)
0270618
79.9%
132878
 
9.7%
214989
 
4.4%
38993
 
2.7%
45844
 
1.7%
ValueCountFrequency (%)
128
 
< 0.1%
1118
 
< 0.1%
1025
 
< 0.1%
983
 
< 0.1%
8219
0.1%

Kyori1Chakukaisu2
Real number (ℝ≥0)

ZEROS

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4099890133
Minimum0
Maximum15
Zeros274489
Zeros (%)81.1%
Memory size2.6 MiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.110328238
Coefficient of variation (CV)2.708190225
Kurtosis19.89095999
Mean0.4099890133
Median Absolute Deviation (MAD)0
Skewness3.91709421
Sum138819
Variance1.232828797
MonotocityNot monotonic
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0274489
81.1%
131143
 
9.2%
215120
 
4.5%
37170
 
2.1%
44394
 
1.3%
52794
 
0.8%
61631
 
0.5%
71161
 
0.3%
9238
 
0.1%
8214
 
0.1%
Other values (3)238
 
0.1%
ValueCountFrequency (%)
0274489
81.1%
131143
 
9.2%
215120
 
4.5%
37170
 
2.1%
44394
 
1.3%
ValueCountFrequency (%)
1538
 
< 0.1%
1143
 
< 0.1%
10157
< 0.1%
9238
0.1%
8214
0.1%

Kyori1Chakukaisu3
Real number (ℝ≥0)

ZEROS

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3977235138
Minimum0
Maximum11
Zeros269400
Zeros (%)79.6%
Memory size2.6 MiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.006800985
Coefficient of variation (CV)2.531409257
Kurtosis16.60083256
Mean0.3977235138
Median Absolute Deviation (MAD)0
Skewness3.604890406
Sum134666
Variance1.013648222
MonotocityNot monotonic
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0269400
79.6%
137085
 
11.0%
215590
 
4.6%
37728
 
2.3%
44680
 
1.4%
52099
 
0.6%
6951
 
0.3%
7545
 
0.2%
8276
 
0.1%
9131
 
< 0.1%
Other values (2)107
 
< 0.1%
ValueCountFrequency (%)
0269400
79.6%
137085
 
11.0%
215590
 
4.6%
37728
 
2.3%
44680
 
1.4%
ValueCountFrequency (%)
1124
 
< 0.1%
1083
 
< 0.1%
9131
 
< 0.1%
8276
0.1%
7545
0.2%

Kyori1Chakukaisu4
Real number (ℝ≥0)

ZEROS

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3804224553
Minimum0
Maximum12
Zeros268465
Zeros (%)79.3%
Memory size2.6 MiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum12
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9488928606
Coefficient of variation (CV)2.494313486
Kurtosis18.6355804
Mean0.3804224553
Median Absolute Deviation (MAD)0
Skewness3.671280079
Sum128808
Variance0.9003976608
MonotocityNot monotonic
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0268465
79.3%
139524
 
11.7%
216038
 
4.7%
37347
 
2.2%
43852
 
1.1%
51798
 
0.5%
6986
 
0.3%
7257
 
0.1%
8133
 
< 0.1%
963
 
< 0.1%
Other values (3)129
 
< 0.1%
ValueCountFrequency (%)
0268465
79.3%
139524
 
11.7%
216038
 
4.7%
37347
 
2.2%
43852
 
1.1%
ValueCountFrequency (%)
1245
 
< 0.1%
1143
 
< 0.1%
1041
 
< 0.1%
963
< 0.1%
8133
< 0.1%

Kyori1Chakukaisu5
Real number (ℝ≥0)

ZEROS

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3691552074
Minimum0
Maximum9
Zeros266290
Zeros (%)78.6%
Memory size2.6 MiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8966308578
Coefficient of variation (CV)2.4288723
Kurtosis16.55634975
Mean0.3691552074
Median Absolute Deviation (MAD)0
Skewness3.535117855
Sum124993
Variance0.8039468951
MonotocityNot monotonic
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0266290
78.6%
143621
 
12.9%
215510
 
4.6%
37560
 
2.2%
42659
 
0.8%
51720
 
0.5%
6647
 
0.2%
7258
 
0.1%
8195
 
0.1%
9132
 
< 0.1%
ValueCountFrequency (%)
0266290
78.6%
143621
 
12.9%
215510
 
4.6%
37560
 
2.2%
42659
 
0.8%
ValueCountFrequency (%)
9132
 
< 0.1%
8195
 
0.1%
7258
 
0.1%
6647
 
0.2%
51720
0.5%

Kyori1Chakukaisu6
Real number (ℝ≥0)

ZEROS

Distinct46
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.863933584
Minimum0
Maximum49
Zeros123166
Zeros (%)36.4%
Memory size2.6 MiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile13
Maximum49
Range49
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.749663251
Coefficient of variation (CV)1.658440432
Kurtosis12.99246207
Mean2.863933584
Median Absolute Deviation (MAD)1
Skewness3.121658865
Sum969705
Variance22.559301
MonotocityNot monotonic
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0123166
36.4%
169793
20.6%
241438
 
12.2%
323954
 
7.1%
415640
 
4.6%
510708
 
3.2%
69059
 
2.7%
76780
 
2.0%
86189
 
1.8%
94415
 
1.3%
Other values (36)27450
 
8.1%
ValueCountFrequency (%)
0123166
36.4%
169793
20.6%
241438
 
12.2%
323954
 
7.1%
415640
 
4.6%
ValueCountFrequency (%)
494
 
< 0.1%
4711
 
< 0.1%
4625
< 0.1%
4428
< 0.1%
4246
< 0.1%

Kyori2Chakukaisu1
Real number (ℝ≥0)

ZEROS

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3380558312
Minimum0
Maximum9
Zeros282190
Zeros (%)83.3%
Memory size2.6 MiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9235959678
Coefficient of variation (CV)2.732081161
Kurtosis14.10504725
Mean0.3380558312
Median Absolute Deviation (MAD)0
Skewness3.47914112
Sum114463
Variance0.8530295117
MonotocityNot monotonic
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0282190
83.3%
126934
 
8.0%
213148
 
3.9%
38879
 
2.6%
44424
 
1.3%
51836
 
0.5%
6791
 
0.2%
7224
 
0.1%
888
 
< 0.1%
978
 
< 0.1%
ValueCountFrequency (%)
0282190
83.3%
126934
 
8.0%
213148
 
3.9%
38879
 
2.6%
44424
 
1.3%
ValueCountFrequency (%)
978
 
< 0.1%
888
 
< 0.1%
7224
 
0.1%
6791
0.2%
51836
0.5%

Kyori2Chakukaisu2
Real number (ℝ≥0)

ZEROS

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3305689443
Minimum0
Maximum11
Zeros285898
Zeros (%)84.4%
Memory size2.6 MiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9684944275
Coefficient of variation (CV)2.929780441
Kurtosis19.90261886
Mean0.3305689443
Median Absolute Deviation (MAD)0
Skewness4.005928039
Sum111928
Variance0.9379814561
MonotocityNot monotonic
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0285898
84.4%
124776
 
7.3%
212629
 
3.7%
37107
 
2.1%
44085
 
1.2%
52113
 
0.6%
61037
 
0.3%
7515
 
0.2%
8220
 
0.1%
10127
 
< 0.1%
Other values (2)85
 
< 0.1%
ValueCountFrequency (%)
0285898
84.4%
124776
 
7.3%
212629
 
3.7%
37107
 
2.1%
44085
 
1.2%
ValueCountFrequency (%)
1123
 
< 0.1%
10127
 
< 0.1%
962
 
< 0.1%
8220
0.1%
7515
0.2%

Kyori2Chakukaisu3
Real number (ℝ≥0)

ZEROS

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.31704234
Minimum0
Maximum10
Zeros282762
Zeros (%)83.5%
Memory size2.6 MiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8862892246
Coefficient of variation (CV)2.795491683
Kurtosis16.86552508
Mean0.31704234
Median Absolute Deviation (MAD)0
Skewness3.742892054
Sum107348
Variance0.7855085897
MonotocityNot monotonic
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0282762
83.5%
129431
 
8.7%
213004
 
3.8%
36713
 
2.0%
43555
 
1.0%
51929
 
0.6%
6687
 
0.2%
7370
 
0.1%
896
 
< 0.1%
925
 
< 0.1%
ValueCountFrequency (%)
0282762
83.5%
129431
 
8.7%
213004
 
3.8%
36713
 
2.0%
43555
 
1.0%
ValueCountFrequency (%)
1020
 
< 0.1%
925
 
< 0.1%
896
 
< 0.1%
7370
0.1%
6687
0.2%

Kyori2Chakukaisu4
Real number (ℝ≥0)

ZEROS

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3119299924
Minimum0
Maximum11
Zeros280426
Zeros (%)82.8%
Memory size2.6 MiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8511907693
Coefficient of variation (CV)2.728787837
Kurtosis17.69102222
Mean0.3119299924
Median Absolute Deviation (MAD)0
Skewness3.747820142
Sum105617
Variance0.7245257257
MonotocityNot monotonic
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0280426
82.8%
132937
 
9.7%
212966
 
3.8%
36396
 
1.9%
43370
 
1.0%
51506
 
0.4%
6620
 
0.2%
7233
 
0.1%
891
 
< 0.1%
1124
 
< 0.1%
ValueCountFrequency (%)
0280426
82.8%
132937
 
9.7%
212966
 
3.8%
36396
 
1.9%
43370
 
1.0%
ValueCountFrequency (%)
1124
 
< 0.1%
923
 
< 0.1%
891
 
< 0.1%
7233
 
0.1%
6620
0.2%

Kyori2Chakukaisu5
Real number (ℝ≥0)

ZEROS

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3001045506
Minimum0
Maximum9
Zeros279296
Zeros (%)82.5%
Memory size2.6 MiB

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8088997821
Coefficient of variation (CV)2.695393257
Kurtosis18.94929915
Mean0.3001045506
Median Absolute Deviation (MAD)0
Skewness3.82847171
Sum101613
Variance0.6543188576
MonotocityNot monotonic
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0279296
82.5%
135416
 
10.5%
213756
 
4.1%
35556
 
1.6%
42363
 
0.7%
51351
 
0.4%
7406
 
0.1%
6320
 
0.1%
8104
 
< 0.1%
924
 
< 0.1%
ValueCountFrequency (%)
0279296
82.5%
135416
 
10.5%
213756
 
4.1%
35556
 
1.6%
42363
 
0.7%
ValueCountFrequency (%)
924
 
< 0.1%
8104
 
< 0.1%
7406
 
0.1%
6320
 
0.1%
51351
0.4%

Interactions

Correlations

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

A simple visualization of nullity by column.
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

Jyotai11Chakukaisu4Jyotai11Chakukaisu5Jyotai11Chakukaisu6Jyotai12Chakukaisu1Jyotai12Chakukaisu2Jyotai12Chakukaisu3Jyotai12Chakukaisu4Jyotai12Chakukaisu5Jyotai12Chakukaisu6Kyori1Chakukaisu1Kyori1Chakukaisu2Kyori1Chakukaisu3Kyori1Chakukaisu4Kyori1Chakukaisu5Kyori1Chakukaisu6Kyori2Chakukaisu1Kyori2Chakukaisu2Kyori2Chakukaisu3Kyori2Chakukaisu4Kyori2Chakukaisu5
000000000033013700000
100000000033013700000
200000000033013700000
300000000033013700000
400000000033432800000
500000000033432800000
600000000033432800000
700000000033432800000
800000000033432800000
900000000033432800000

Last rows

Jyotai11Chakukaisu4Jyotai11Chakukaisu5Jyotai11Chakukaisu6Jyotai12Chakukaisu1Jyotai12Chakukaisu2Jyotai12Chakukaisu3Jyotai12Chakukaisu4Jyotai12Chakukaisu5Jyotai12Chakukaisu6Kyori1Chakukaisu1Kyori1Chakukaisu2Kyori1Chakukaisu3Kyori1Chakukaisu4Kyori1Chakukaisu5Kyori1Chakukaisu6Kyori2Chakukaisu1Kyori2Chakukaisu2Kyori2Chakukaisu3Kyori2Chakukaisu4Kyori2Chakukaisu5
33858200000000000100000000
33858300000000000000100000
33858400000000001000200000
33858500000000000000000000
33858600000000000000000000
33858700000000000000100000
33858800000000000000042330
33858900000000000000200000
33859000000000000000100000
33859100000000000000000000

Duplicate rows

Most frequent

Jyotai11Chakukaisu4Jyotai11Chakukaisu5Jyotai11Chakukaisu6Jyotai12Chakukaisu1Jyotai12Chakukaisu2Jyotai12Chakukaisu3Jyotai12Chakukaisu4Jyotai12Chakukaisu5Jyotai12Chakukaisu6Kyori1Chakukaisu1Kyori1Chakukaisu2Kyori1Chakukaisu3Kyori1Chakukaisu4Kyori1Chakukaisu5Kyori1Chakukaisu6Kyori2Chakukaisu1Kyori2Chakukaisu2Kyori2Chakukaisu3Kyori2Chakukaisu4Kyori2Chakukaisu5count
00000000000000000000077425
7670000000000000010000040202
11040000000000000020000019084
1289000000000000003000008468
1377000000000000004000003507
1000000000000000000012926
4000000000000000000102113
1586000000000000011000002059
1423000000000000005000001712
1876000000000000101000001574